1. Baseline glutamate and GABA concentrations predict task-induced deactivation in the default mode network (DMN) Deactivation of the human brain's DMN is regarded as suppression of endogenous activity to support exogenous task-related processes, and insufficient DMN deactivation has been implicated in several neuropsychiatric disorders. However, the neurochemical mechanism of the DMN's deactivation remains largely unknown. In the present study, we test the hypothesis that the major excitatory and inhibitory neurotransmitters, glutamate and GABA, respectively, are associated with DMN deactivation. We used MR spectroscopy to measure neurotransmitter concentrations in the posterior cingulate cortex/precuneus (PCC/PCu), a key component of the DMN, and functional MRI to evaluate DMN deactivation induced by an n-back working memory task. Our results demonstrate significant associations of glutamate and GABA with DMN deactivation. Specifically, high regional GABA concentration in the PCC/PCu area is associated with enhanced deactivation induced by the task in the same region, whereas high glutamate concentration is associated with reduced deactivation. Furthermore, the association between GABA and DMN deactivation increases with the cognitive loads. These neurochemical characteristics of DMN deactivation may provide novel insights toward better understanding of the DMN's functions under normal physiological conditions and dysfunctions in neuropsychiatric disorders. (Journal of Neuroscience 33:18566-18573, 2013.) 2. Detecting resting-state brain activity by spontaneous cerebral blood volume (CBV) fluctuations using whole brain vascular space occupancy imaging. This study demonstrated that resting-state brain activity can be reliably detected by spontaneous fluctuations of CBV-weighted signal using whole-brain vascular space occupancy (VASO) imaging. Specifically, using independent component analysis, intrinsic brain networks, including default mode, salience, executive control, visual, auditory, and sensorimotor networks were revealed robustly by the VASO technique. We further demonstrate that task-evoked VASO signal aligned well with expected gray matter areas, while blood-oxygenation level dependent (BOLD) signal extended outside of these areas probably due to their different spatial specificity. Moreover, we showed that the VASO images had reduced susceptibility-induced signal voiding, compared to the BOLD technique. Consequently VASO-based functional connectivity signals were well preserved in brain regions such as orbital frontal cortex. Our study suggests that VASO imaging, with its improved spatial specificity and less sensitivity to susceptibility artifacts, may have advantages in resting-state fMRI studies. (Neuroimage 84:575-584, 2014.) 3. Large-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function This study tested the hypothesis that the strength of coupling among 3 large-scale brain networkssalience, executive control, and default modewill reflect the state of nicotine withdrawal (vs smoking satiety) and will predict abstinence-induced craving and cognitive deficits. We developed a resource allocation index (RAI) that reflects the combined strength of interactions among the 3 large-scale networks. The RAI was significantly lower in the abstinent compared with the smoking satiety states, suggesting weaker inhibition between the default mode and salience networks. The reduced RAI predicted abstinence-induced cravings to smoke and less suppression of default mode activity during performance of a subsequent working memory task. Alterations in coupling of the salience and default mode networks and the inability to disengage from the default mode network may be critical in cognitive/affective alterations that underlie nicotine dependence. (JAMA Psychiatry 71(5): 523530, 2014). 4. Resting state functional connectivity (rsFC) of striatal network in cocaine users While dysregulated striatal-cortical network interactions have been identified in cocaine addiction, the association between these brain networks and key addiction-related behaviors such as impulsivity and compulsivity is poorly understood. We tested the hypothesis that cocaine addiction is associated with disturbances in striatal-cortical communication as captured by rsFC. We also explored the relationships between striatal rsFC, impulsivity and compulsivity in cocaine addiction. Increased rsFC strength was observed predominantly in striatal-frontal circuits while decreased rsFC was found in striatal-cingulate, striatum, -temporal, -hippocampus and -insula circuits in the CU group compared with the HCs. Increased striatal- dorsal lateral prefrontal cortex connectivity strength was positively correlated with recent cocaine use and elevated impulsivity in the CUs while the balance between striatal- dorsal anterior cingulate cortex and striatal- inferior prefrontal cortex circuits was significantly associated with cocaine compulsive behaviors. (Under revision) 5. Hippocampal basal regional cerebral blood flow (rCBF) and resting-state functional connectivity (rsFC) predicts cocaine relapse Identification of individual differences predicting relapse or remission following treatment would provide a more rational targeting of mechanisms associated with relapse risk. In this study with a population of cocaine-dependent participants scanned just prior to discharge from a residential treatment program, we utilized rCBF to identify local neuronal activity alterations as a function of relapse status. We then used this regional alteration as a seed region in the rsFC analysis to identify those functional circuits driven by this local change in neuronal activity with the hypothesis that such circuits may serve as relapse predictors. Cocaine-dependent participants who relapsed quickly (i.e. within 30 days) following treatment discharge were distinguished by increased resting rCBF in left posterior hippocampus (pHp) and increased rsFC strength between pHp and posterior cingulate cortex (PCC). Both findings significantly predicted days to relapse over a six-month period; the prediction power was strengthened when the two measures were considered concurrently. The identification of both pHp activity and pHp-PCC functional connectivity as independent predictors of relapse, coupled with the extant literature, support further explorations of the interaction between personalized, contextual cravings and the default mode network upon relapse. (Under review) 6. Topologically reorganized connectivity architecture of default-mode, executive-control and salience networks across working memory task loads The human brain is topologically organized into a set of spatially-distributed, functionally-specific networks. Of these networks, the default-mode network (DMN), executive-control network (ECN) and salience network (SN) have been shown to play vital roles in cognitive functions. However, very little is known about whether and how the interactions within and between these networks would be modulated by cognitive demands. Here, we employed graph-based modularity analysis to identify the DMN, ECN and SN during an N-back working memory (WM) task and further investigated the modulation of intra- and inter-network interactions at different cognitive loads. As the task load elevated, functional connectivity decreased within the DMN while increased within the ECN; and the SN connected more with both the DMN and ECN. Within-network connectivity of the ventral and dorsal posterior cingulate cortex was differentially modulated by cognitive load. Further, the superior parietal regions in the ECN showed increased inter-network connections at higher WM loads and these increases correlated positively with WM task performance. (Under review)